Cross-border data transfers—involving both personal and nonpersonal data—enable firms of all sectors and sizes to engage in transatlantic commerce. Government agencies also need firms to be able to transfer data across borders as part of financial oversight, drug approval, law enforcement, counterterrorism, and other responsibilities. The European Union’s (EU) General Data Protection Regulation (GDPR) was supposed to bring a more predictable and harmonized approach to data protection within the EU and provide a range of tools for firms to transfer EU personal data overseas. Instead, successive court challenges have made it harder and more complex—and without political intervention, the situation will devolve into an irrevocably severed transatlantic digital relationship. EU and U.S. policymakers need to step in and avoid taking a narrow and legalistic approach to the challenges facing transatlantic data flows and instead build back better in terms of creating a new and efficient transatlantic data framework.
Transatlantic digital policy cooperation has faced a decade of turmoil—but it has never been as dire as now. For the second time, the EU’s top court (in the Schrems II case) invalidated the framework that manages transatlantic transfers of EU personal data (the EU-U.S. Privacy Shield), after finding that U.S. laws do not sufficiently protect data about EU citizens stored in the United States. The challenge for policymakers is to reconcile the EU’s data protection laws with U.S. surveillance policies and practices. Unfortunately, the current stalemate makes transatlantic data transfers increasingly difficult, if not impossible, and imperils other major transatlantic interests around commercial access to data for trade and innovation and government cooperation on law enforcement, national security, and regulatory issues.
It is impossible to fully localize any digital process, good, or service without some level of impact or disruption. The underlying data storage infrastructure does not necessarily rely on the ability to exchange data across borders, but the services built on it certainly do.
Potential legal challenges and restrictive policy proposals by the European Data Protection Board (EDPB) and others are raising concerns about whether firms will still be able to use standard contractual clauses (SCCs), which are the last broadly accessible legal tool for U.S. and EU firms to transfer EU personal data. Indicative of where this is heading, the EDPB has already issued guidance that “strongly encourages” EU institutions considering new contracts with service providers “to avoid processing activities that involve transfers of personal data to the United States.” Another major (and restrictive) policy reaction is making firms (no matter how big or small) responsible for assessing each storage destination’s surveillance and government access laws—and that the hypothetical potential for any data disclosure is reason enough to not transfer EU personal data. This is an unrealistic legal and practical threshold for firms to meet given it fails to account for the actual potential of government access and the difficulty in understanding different and constantly changing legal frameworks around the world.
Transatlantic data flows may be suddenly severed through another legal challenge or reduced over time as new restrictive requirements are defined and enforced against firms by the EDPB and individual EU member state data protection authorities. Within this challenge of rebuilding the transatlantic digital relationship, it is important to reinforce the central point that data transfers, data-driven innovation, and data protection are not mutually exclusive. Firms cannot undermine local data privacy, protection, and other related laws by transferring data to another country because they are held accountable for how they manage data, meaning local legal requirements travel with the data, regardless of where it is stored and processed. This contrasts with the European focus on the geography of data storage. Making international transfers of EU personal data increasingly difficult, costly, and legally uncertain leaves local data storage and processing as the only viable option, which is the end goal for many privacy advocates and policymakers in Europe. As it stands, the EU’s approach to data privacy is creating the world’s largest de facto data localization framework. The EU’s only peer is China’s broad and growing explicit data localization regime, with laws that make local data storage and processing the norm and transfers the exception. At some point, the pressure on U.S. policymakers to reciprocate with equally restrictive rules preventing EU firms such as Volkswagen, Phillips, Siemens, and Sanofi from transferring data from their U.S. operations to their EU headquarters will become significant enough to spur retaliatory action.
It is infeasible for firms to build out local human resources, management, research and development (R&D), regulatory compliance, and information technology (IT) and customer support services in each and every market that has local data storage requirements. Such requirements undermine the ability of all firms—especially globally engaged ones—to leverage the distributed power of the Internet and centralized IT systems to manage local, regional, and global business operations and compliance activities. It is impossible to fully localize any digital process, good, or service without some level of impact or disruption. While it may be technically possible for a company—particularly a large one—to fully localize data storage, there would be major disruptions and changes to the type and quality of services, as well as limits on the use of technologies such as artificial intelligence (AI) wherein algorithms improve with larger datasets. The underlying data storage infrastructure does not necessarily rely on the ability to exchange data across borders, but the services built on it certainly do.
Transatlantic data flows have enormous economic implications. Two-way EU-U.S. digital trade grew from an estimated $166 billion in 2005 to $292 billion in 2015. The sectoral case studies in this report show what is at stake. Despite the popular misconception that data flows only benefit search engines and social networks, severing transatlantic data flows would have wide-reaching impacts across the global economy. Yet, some EU policymakers think that restricting or cutting off data flows and digital trade with the United States is a good thing as it aligns with their “digital sovereignty” goals, believing that if it hurts leading U.S. tech firms, then it must be good—without realizing or appreciating the broader and much larger costs. This stance ignores the fact that doing so would also hurt the hundreds of European firms that used Privacy Shield and SCCs to manage data transfers between their headquarters and offices and operations in the United States. Unfortunately, this protectionist impulse is also evident in Europe’s ongoing effort to define its own digital economy framework, such as the European Commission’s data strategy and its Data Governance Act.
But the impact is not only trade and innovation-related—governments on both sides of the Atlantic depend on firms being able to transfer data as part of day-to-day regulatory requirements, whether for financial oversight of the banking, financial, and payments sectors (for financial stability, counter-terrorism financing, or anti-money-laundering purposes) or the review of clinical trials by respective public health agencies. This is obviously in addition to law enforcement and national security cooperation.
This report starts by outlining the history of the transatlantic digital relationship to show how both the EU and Unites States have continuously recognized the value in working together to address issues as they arise. However, this report also makes the case that this relationship should not be based on troubleshooting, but ideally, on a broader digital agenda, given both sides share many values and interests. It then analyzes estimates of the economic value of transatlantic digital trade, before providing a series of sectoral case studies to show how firms in a diverse range of sectors—from automotive and other advanced manufacturers to life sciences to consumer Internet services to financial and banking services—use transatlantic data flows.
Finally, this report provides recommendations to build a better, stronger, and broader transatlantic digital relationship:
- Policymakers should negotiate a new Privacy Shield. Long term, the two sides could work toward legislation and a treaty agreement that would codify some of their commitments. In an ideal world, the United States and Europe would work together with like-minded countries to develop a “Geneva Convention for Data,” which would create consensus on issues around government access to data.
- The EU should redouble efforts to build new data transfer mechanisms under GDPR. This would be in addition to the more immediate need to make existing legal tools (SCCs and binding corporate rules) clear, reasonable, and accessible.
- The United States and EU should conclude negotiations to improve transatlantic access to electronic evidence for law enforcement investigations.
- The EU and United States should build a broader agenda for pragmatic cooperation on data and digital policy issues—one based on “digital realpolitik.” Such cooperation would be economically beneficial to both sides given their extensive economic connections. Furthermore, while there are points of conflict, overall, their shared values stand in stark contrast to those of authoritarian digital powers such as China and Russia. Such an agenda could work on how to develop data sharing frameworks; develop and apply the appropriate regulation of AI, such as via algorithmic accountability; develop interoperable electronic identity systems; build pre-standardization cooperation for new and emerging technologies; develop a coordinated strategy to counter China’s efforts to unduly influence international standards setting for AI and digital policies; and cooperate and coordinate investment screening and export controls that increasingly deal with data and digital technologies.
Despite constant pressure over the last decade—and as reactions to the Snowden revelations continue to reverberate—both the EU and United States have kept the transatlantic data and digital relationship going. Despite the challenges, there is largely bipartisan support in the United States for EU-U.S. digital engagement.
There was substantial continuity across the Obama and Trump administrations, which is likely to continue in the Biden administration. In 2014, President Obama issued presidential policy directive number 28 on “Signals Intelligence Activities,” which included safeguards for non-U.S. persons in signals intelligence. Privacy Shield was signed under President Obama, and was also supported by the Trump administration. The U.S. Federal Trade Commission enforced Privacy Shield throughout both administrations. Meanwhile, the U.S. Congress continues to debate a comprehensive U.S. data privacy bill that would no doubt improve the overall context for engagement with the EU. However, data privacy legislation would not address the fundamental disagreement over U.S. government surveillance that is at the heart of Schrems II.
Without political intervention, it is likely that transatlantic data transfers will eventually be cut off.
Given this, rebuilding a strong transatlantic relationship will require action on both sides. Most of the focus has been on the United States, which has already made changes to account for EU concerns and signaled its willingness to consider further changes. Yet, ongoing conflict over EU policy remains. The United States should take into consideration European concerns as it updates its laws and policies around government access to data and data protection. However, the EU should also consider policy and legal reforms to GDPR and other digital policies as part of constructive efforts to build both short- and long-term tools to address both new and ongoing issues regarding international data governance. EU member states also need to be consistent in addressing data privacy and surveillance issues. National security is not a European Commission or EU competency, so doing so will require EU member engagement. If the EU continues to take a largely hands-off approach about the need to address all related issue—not just privacy, but trade and national security—it will lead to ruin as it leaves privacy advocates, the EDPB, and the courts in the driver’s seat of a critically important part of the transatlantic relationship. Without political intervention, it is likely that transatlantic data transfers will eventually be cut off.
The stakes involved in building a successful transatlantic digital relationship are already high, but they grow even higher, given the many global debates about data and digital technologies. If the EU and United States want to truly work together on these issues—as the European Commission frequently calls for—they both need to show that they can address their own issues in a way that presents a model for other countries. Absent such an outcome, calls for transatlantic cooperation on global issues would be seen as meaningless.
Digital trade—including both digital and digitally enabled services—is an increasingly important component of the global economy. As the sectoral case studies show, cross-border transfers of data underpin virtually all business processes in international trade and investment.
Estimating the value of transatlantic data flows and digital trade is challenging. For example, approximating value by the aggregate volume of data transfers has significant limitations. The value of data depends on its content. Data is also highly context specific. An individual person’s data may be valuable to that person, but only hold broader value when aggregated with data from many other individuals and other sources of data. The value of data is temporal in that it may only become valuable when used as part of future analysis. Furthermore, some data flows may be non-monetized—representing intra-company transfers that are commercially valuable, but not captured in a formal transaction. Similarly, gross domestic product (GDP) and other economic statistics do not measure the value of consumer surplus, such as when consumers access digital goods and services at no financial cost. While estimating the value of the specific underlying data and its transfer is difficult, it is clear that continuous data aggregation and analysis by firms creates enormous value, in what the Organization for Economic Cooperation and Development (OECD) calls the “global data value cycle.”
While precise, comprehensive, and consistent measurement of the value of data and digital trade in and between the United States and EU is not yet possible, there are a range of estimates that support what we know anecdotally—that data and digital trade represent an important and fast-growing part of the global economy. In August 2020, the U.S. Department of Commerce’s report “New Digital Economy Estimates” calculated that the digital economy accounted for 9 percent of U.S. GDP in 2018, which ranked it just below the manufacturing sector (which accounted for 11.3 percent) and just above finance and insurance (7.6 percent). From 2006 to 2018, the U.S. digital economy’s real value added grew at an annual rate of 6.8 percent. It supported 8.8 million jobs, which represented 5.7 percent of U.S. total employment. In Europe, the value added from the information and communication technology (ICT) sector in 2017 was equivalent to at least 3.9 percent of GDP, 2.5 percent of total employment, and 18.6 and 20.6 percent of the total R&D personnel and researchers in the EU, respectively. Employment in the EU’s ICT services sector grew by 22.7 percent between 2012 and 2017. And as of 2020, one of the fastest-growing aspects of the global digital economy, the “app economy,” accounts for over 2 million jobs in the U.S. and EU alike.
Data and digital trade represent an important and fast-growing part of the global economy.
Traditional trade statistics capture some of the EU-U.S. digital trade relationship, but not all. The United States is both the largest (non-EU) market for Europe’s digitally enabled services and its largest supplier. Indicative of this, about half of all data flows in both the United States and Europe are transatlantic transfers. In 2018, digitally enabled services accounted for the majority of U.S. services exports (55 percent), nearly half of U.S. services imports (48 percent), and a full 69 percent of U.S. global surplus in services. The U.S. also accounted for 32 percent of exports and 39 percent of imports of digitally enabled services from and to the EU.
The U.S. Department of Commerce’s ICT and potential-ICT based digital trade data provides the broadest, and most recent, estimate of transatlantic digital trade, which in total, was worth $295 billion in 2018. It captures both ICT services that are used to facilitate information processing and communication (e.g., computer and telecommunication services) and potentially ICT-enabled services that can predominantly be delivered remotely over ICT networks, such as financial, insurance, intellectual property, professional and management services, and R&D services, among others. The data estimates that, in 2018, ICT and potential-ICT based digital trade between the United States and Europe was $188 billion in exports to, and $107 billion in imports from, the EU, respectively (see figure 1).
Figure 1: U.S. exports and imports of ICT and potential ICT-based digital trade with the EU (2018)
Updating the U.S. Department of Commerce’s “digitally deliverable services” (DDS) estimate—which comprises a more narrow set of services than those included in the estimates above—is more readily comparable across countries (using trade in value added (TiVA) and Eurostat databases), but does not have data for recent years (most recent data is for 2015). Analysis of DDS trade captures a mix of transactions that are entirely digital, somewhat digital, or entirely non-digital. It also shows that transatlantic trade is large and growing. U.S. DDS exports to the EU rose from $98 billion to $183 billion between 2005 and 2015, while EU DDS exports to the United States rose from $67 billion to $108 billion (see figure 2).
Figure 2: U.S. exports and imports of digitally delivered services with the EU (2005-1015)
The EU’s DDS exports vary considerably by member state, which highlights the economic differences between member states and their use of data, services, and ICTs. According to TiVA data, Germany has seen consistently rising DDS exports, growing from $36 billion in 2010 to $65 billion in 2018 (see figure 4). France has also seen its DDS exports grow, from $27 billion in 2011 to $41 billion in 2018 (see figure 5). By contrast, Italy’s exports have barely grown (see figure 6), increasing only from $6.1 billion to $8.6 billion between 2010 and 2018. The Netherlands’ DDS exports declined, falling from $41 billion in 2010 to $26 billion to 2018. Despite that country’s low overall DDS exports, however, DDS services remain important to the Netherlands, exhibiting a high degree of DDS export intensity (DDS exports as a percentage of total service exports).
Parsing out DDS exports by industry shows further variation between the United States and the EU. In the United States, “other” DDS exports, represented by services (e.g., the legal, scientific, and architectural fields), has dominated in recent years (see figure 3). Royalties and licensing, as well as financial services, are also both significant drivers of DDS exports. IT services dominate in Germany (growing from $11.6 billion in 2012 to $22 billion in year 2018), while “other” remains at a close second, indicating a heavy IT focus in Germany relative to other EU countries (see figure 4). In France, licensing and “other” services take the lead, followed by IT and financial services (see figure 5). IT services also dominate in Italy, with that sector outweighing licensing and “other” related DDS exports (see figure 6). The EU will continue to remain a key region for many DDS sectors going forward, rivaled by the United States, Japan, and increasingly, China.
Figure 3: U.S. exports of digitally delivered services globally, by product group (2010-2018)
Figure 4: Germany’s exports of digitally delivered services outside the EU, by product group (2010-2018)
Figure 5: France’s exports of digitally delivered services outside the EU, by product group (2011-2018)
Figure 6: Italy’s exports of digitally delivered services outside the EU, by product group (2010-2018)
A comprehensive assessment of transatlantic digital trade needs to take into account valuable (but non-monetized) intra-firm data transfers that represent services supplied via affiliates located in both Europe and the United States. As in 2018, about two-thirds of the services provided internationally both by and to the United States were through affiliates. Many (if not all) multinational companies in the United States and EU rely on cross-border data transfers to support their international business operations. Again, there are measurement issues as differences in coverage and classification make it difficult to compare trade in services with services supplied through affiliates. However, they are still useful in showing that the data displayed in figure 5 and figure 6 are conservative estimates of the full value of digital and digitally enabled services in the transatlantic economic relationship.
A comprehensive assessment of transatlantic digital trade needs to take into account valuable (but non-monetized) intra-firm data transfers that represent services supplied via affiliates located in both Europe and the United States.
The U.S. Department of Commerce estimated that 53 percent of the $839 billion in services provided in Europe by U.S. affiliates in 2017 was digitally enabled. That year, U.S. affiliates in Europe supplied $444 billion in digitally enabled services, whereas European affiliates in the United States supplied only $269 billion in digitally enabled services. The United States enjoys continued trade surpluses with the EU in many key digitally enabled services delivered via affiliates. For example, in 2018, U.S. software firms exported over $51 billion worth of services to the EU, whereas the United States only imported around $3.6 billion worth of software services from the EU. However, the EU did have advantages in areas such as management consulting, where it enjoyed a $4.9 billion surplus vis-à-vis the United States (see figure 7).
Figure 7: U.S.-EU trade surpluses in key digitally enabled services by affiliates (2018)
Transatlantic data flows and digital trade matter to a broad range of sectors, and are a critical complement to the use of traditional trade statistics in understanding the role and value of data transfers.
Industrial, Transport, and Automotive Sectors: Of Machines and Data
IT is transforming global manufacturing by digitizing virtually every step in how products are designed, fabricated, transported, serviced, and used—a phenomenon called “smart manufacturing” in the United States and “Industry 4.0” in Europe. Indicative of this, as of 2017, digital services provided an estimated 25 percent of manufacturing inputs. The increasingly global nature of manufacturing design, production, and customer and after-sales support processes mean that modern manufacturing firms increasingly rely on cross-border data flows. This section outlines how automotive and industrial firms rely on data and data flows, including a detailed analysis of the automotive sector and case studies on Scania and Volkswagen.
The global race for innovation advantage in modern manufacturing comes down, in no small part, to how firms and their broader production network are able to integrate data from all relevant stakeholders—wherever they are around the world. As part of this race, the United States and Europe have much to share and benefit from in terms of integrating digital manufacturing operations and associated services. German President Angela Merkel has directly engaged in promoting Industry 4.0, noting, “We have reached a critical moment, a point where the digital agenda is fusing with industrial production.” She’s also identified the failure to lead in smart manufacturing as a threat to Germany’s industrial prowess, “We have to execute quickly, otherwise those who are already leading in digital will snatch the industrial production from us.” Europe regards smart manufacturing as a core component of the European strategy on “smart specialization,” which aims to strengthen the comparative advantage of the EU in terms of ICT skills, R&D capability, industrial output, and infrastructure. In other words, in Europe, smart manufacturing is being pursued at a regional level to make European regional-manufacturing clusters more globally competitive.
Smart manufacturing provides manufacturers with a comprehensive view of what’s occurring at every single point in the production system, along with the insights to make real-time adjustments in order to optimize production. A “plugged in” manufacturer can receive real-time information from suppliers to adapt to supply chain disruptions or use data analytics from across the supply chain to adjust to meet shifting demand. As Robert Hardt, president and CEO of Siemens Canada, explained, smart manufacturing entails nothing less than “the availability of all relevant information in real time, through interconnection of all instances of value creation, and the capacity to derive from this data an optimal value creation flow at any point in time.” Cloud services and data flows level the playing field between small and large firms as it makes it easier for the smaller companies to access best-in-class, enterprise-level software and IT solutions.
Manufacturing, transport, and industrial firms need a legal framework to transfer personal and nonpersonal data just as much as any other sector of the economy. Indicative of this, in October 2020, European trade associations from the road, air, maritime, rail, manufacturing, and logistics sectors outlined how they increasingly rely on the exchange of large amounts of personal and nonpersonal data between multiple actors, and explained why the EU needs to create a clear framework for the governance of these business-to-business data transfers. Building on this, on November 26, 2020, a joint report and survey of nearly 300 firms (mainly EU firms (75 percent) headquartered across 25 countries, from all major industries, and a mix of company sizes) by Business Europe, DIGITAL EUROPE, the European Round Table for Industry, and European Automobile Manufacturers Association found that nearly 85 percent use SCCs. Manufacturing firms represented the second-largest users of SCCs (22 percent), behind firms in the ICT sector.
The role of data flows within the global development of smart manufacturing is best demonstrated by cloud computing; additive manufacturing; sensor technologies and networked machine-to-machine (M2M) devices; data analytics and generative design; new business models involving data-dependent after-sales service; the use of AI for predictive and preventative maintenance and repair; and data-driven global research collaboration.
Cloud computing is transforming virtually every part of modern manufacturing. Even by 2015, a majority of manufacturing firms used cloud applications. Expansive cloud-based networks store and process the massive amount of data necessary to manage modern manufacturing operations. Whether it’s how manufacturing enterprises operate, how they integrate into supply chains, or how products are designed, fabricated, and used by customers, cloud computing is helping manufacturers innovate, reduce costs, and increase their competitiveness. Cloud computing allows manufacturers to use new production systems, from 3D printing and high-performance computing (HPC) to the Internet of Things (IoT) and industrial robots. This “Industrial IoT” increasingly relies on cloud computing and data transfers, as there are a number of individuals, objects, and other sensors connected to a growing network of smart devices and sensors. Cloud computing alongside other foundational technologies such as advanced sensors, HPC, and computer-aided design, engineering, and manufacturing (CAD/CAE/CAM) software represents an essential component of the smart manufacturing revolution. One study estimates that manufacturers allocate an average of 8.1 percent of their R&D budgets to developing these types of digital tools.
Business-to-business and M2M cross-border data flows are powering much of the digital transformation sweeping industrial sectors around the world. These business-to-business data transfers don’t get nearly as much attention as consumer Internet services, but they’re increasingly critical to the global economy. In contrast to the popular perception about the major role played by personal data, individual consumers, and smartphones, Cisco estimated that out of the approximately 18.4 billion networked devices in use in 2018, nearly one-quarter (24 percent) served business customers. Cisco’s Annual Internet Report (2018–2023) outlines how a growing number of M2M applications, such as smart meters, transportation, and package and asset tracking are now major drivers in the growth of Internet-connected devices—and that by 2023, M2M connections will account for about half of the world’s total devices and connections. M2M connections will be the fastest-growing device and connections category (faster than smartphone use), growing nearly 2.4-fold during the forecast period (19 percent compound annual growth rate (CAGR)) to 14.7 billion connections by 2023.
Business-to-business data transfers don’t get nearly as much attention as consumer Internet services, but they’re increasingly critical to the global economy.
Additive manufacturing is becoming more common for product prototyping and some mass production. For example, Ford uses 3D printing to make prototypes of auto parts, including cylinder heads, brake rotors, shift knobs, and vents. In 2014, GE Aviation announced plans to begin mass production of its LEAP 3D-printed jet-engine fuel nozzles. Similarly, Boeing has replaced machining with 3D printing for over 20,000 units of 300 distinct parts. Firms are also using additive manufacturing to personalize products. Both Nike and Under Armour are exploring how additive manufacturing can revolutionize how they manufacture footwear, ultimately allowing the shoemakers to customize a sneaker to each athlete’s foot. 3D printing allows Nike to produce a shoe with just a few parts instead of dozens, resulting in up to 80 percent less waste. Siemens uses additive manufacturing to create in-the-ear hearing aids that are individually adapted to the wearer’s auditory canal. The prosthetics industry has been revolutionized by 3D-printed limbs tailored to patients’ specific structural needs and design desires.
Data analytics, machine learning, and AI improve operations across industrial firms—not just on the factory floor. For example, data-driven insights can enable more innovative and efficient product design processes. “Generative design,” a process by which a computer algorithm tests thousands (or even millions) of design possibilities based on parameters entered by designers or engineers, accelerates innovation by rapidly generating possibilities that humans alone may not have discovered. Human-machine interaction can also improve production processes, as workers collaborating with automated machines allows for more dynamic and adaptive processes. In each of these approaches, data flows are necessary to enable cross-border, multi-team collaboration.
Data flows also allow for critical after-sales service and manufacturers to create new services-based business models. For example, maintenance crews can receive diagnostics from an airplane while it’s still in-flight, and vehicle manufacturers can remotely monitor their products and alert drivers when repairs are needed. It’s becoming more common for manufacturing firms to eschew selling individual products in favor of selling products as integrated services. For example, GE’s medical devices division no longer sells individual radiological equipment (e.g., MRI or X-ray machines) to hospitals; rather, it sells radiological services, taking over management of a hospital’s entire suite of radiological assets and installing devices with remote-monitoring capabilities that allow GE to both monitor whether they are operating and functioning properly and diagnose and detect maintenance issues. Similarly, Kaeser Kompressoren, a German-based manufacturer of compressed air systems and services, launched an “air-as-a-service” business model in which customers no longer purchase Kaeser compressors but rather lease the compressors and pay only for the compressed air itself. It means customers can scale consumption up or down as the needs of their manufacturing operations change, without needing to purchase new equipment.
One of smart manufacturing’s biggest benefits is in predictive and preventative maintenance and repair, which allows firms to shift from a maintenance model of “repair and replace” to “predict and prevent.” The McKinsey Global Institute has estimated that the use of predictive maintenance techniques reduces factory equipment maintenance costs by up to 40 percent, while reducing equipment downtime by up to 50 percent, and capital-equipment investment costs (to replace defective equipment) by 5 percent. For example, Intel uses predictive modeling to anticipate failures, prioritize inspections, and cut monitoring costs at its chip-manufacturing plants. Manufacturers are also integrating predictive-maintenance data into their enterprise resource planning systems to improve workflow scheduling, thus optimizing repair schedules and minimizing machine downtime. Taleris, which supports airline and cargo-carrier operations, uses this technology to predict aircraft-maintenance faults and thus minimize flight delays. Likewise, Germany’s ThyssenKrupp AG and Kaeser Kompressoren use tens of thousands of networked equipment sensors to identify and predict maintenance issues, which reduces unscheduled downtime and helps avoid unnecessary repair trips.
The Automotive and Transport Sectors Rely on Data Flows to Support Drivers, Connected Vehicles, and Related Services
Digital technologies and data flows are particularly critical to the automotive and transport sector. As Swedish commercial vehicle manufacturer Scania’s Hakan Schildt told the Financial Times in 2018, “[T]ransport is becoming a data business.” As connected devices, data-driven insights, and advancements in AI accelerate innovation in this sector, the ability to exchange data is crucial to improving the quality and safety of vehicles and transportation systems. Cisco’s Annual Internet Report (2018–2023) predicts that connected car applications, which include fleet management, in-vehicle entertainment systems, emergency calling, Internet, vehicle diagnostics, and navigation, will be the fastest-growing category of M2M application, with a 30 percent CAGR. The next generation of trade and innovation between the closely integrated EU-U.S. automotive and transport sectors will be put at risk if the rules and regulations around data are not carefully designed so as to allow the reasonable and responsible collection, processing, and transferring of personal and nonpersonal data associated with connected vehicles.
Automotive and transport manufacturers receive, exchange, and process increasing amounts of both personal and nonpersonal data from individuals and vehicles around the world, including data about the vehicles themselves (e.g., vehicle identification, configurations, maintenance information, and network information such as IP address or Bluetooth name); data about drivers and other users (e.g., driving behavior, geolocation, user-provided information, and contractual data); and data from outside the vehicle (e.g., temperature, weather conditions for automatic lights or wipers, and images and videos from outside the vehicle). For instance, modern vehicles collect map and personal data for real-time analysis and use. Automated and autonomous vehicles rely on AI that uses cameras and sensors to analyze the vehicles’ environment, including detecting road signs and other road users, and then shares that data with the cloud to ensure the information is accurate and the cars operate as safely as possible. Similarly, sensors monitor drivers’ attention and detect drowsiness. Figure 8 is indicative of the data transfers that an EU-headquartered, globally engaged, manufacturing or transport firm would be engaged with in having R&D, human resources, engineering, sales, and customer support centers around the world.
Figure 8: The data transfers for a (generic) EU-headquartered manufacturing/transport firm with global operations