Cybersecurity. Smart manufacturing won’t fulfill its promise without reliable cybersecurity. In our conversation, three themes emerged: First, cybersecurity for operational technology requires a different approach than that for information technology—a distinction not always made by regulators. Second, smaller companies often lag behind larger companies in terms of awareness and adoption of cybersecurity measures, and this hurts all companies in the value chain. Said one executive in the industrial defense supply chain, “I am a big fan of the NIST framework. But small companies are willing to take on more risk than their larger customers. Small and medium enterprises (SMEs) are thus making risk decisions for us.” Third, no single cybersecurity solution can address all vulnerabilities in a typical manufacturing environment, making investment decisions difficult. As one executive concluded, “There will always be multiple products to buy. The trick is knowing which few will get you 80% there.”
Privacy. The executives recognized that ensuring privacy of personal information is an active area of policy making that impacts manufacturers, even those that do not sell directly to individual consumers. When suggesting that a company should just adopt the EU General Data Protection Regulation (GDPR) as a global standard, others argued against it. Although strong in certain respects, GDPR is weak in others. And the US is likely to impose its own standard eventually. The National institute of Standards and Technology (NIST) within the US Department of Commerce has just started its year-long effort to develop a risk-based privacy framework building on the success of its cybersecurity framework. Given differences across companies in the manufacturing sector, a risk management approach was seen as the best approach.
Talent. Smart manufacturing will exacerbate the ongoing “skills gap” in manufacturing. This is a big issue for those seeking to attract employees with skills in such fields as data analytics and AI (including machine learning). A big part of the challenge is cultural; parents do not want their children to pursue a career in manufacturing and those seeking a career in data analytics or AI prefer to work for companies in Silicon Valley. Several of the executives acknowledged a need to make manufacturing “cool” to young adults, especially those who do not believe manufacturing is high-tech.
AI. The emerging consensus among the executives was that AI can be useful in some cases, especially if there’s a human overseer. However, the consequences of a failure in a continuous manufacturing process are so severe that executives have a high degree of trepidation of AI and machine learning as a decision maker absent human oversight. As one executive noted, “Actionable insight is what we need from AI.”
Technical Standards. Smart manufacturing cannot be realized without the emergence of global standards to ensure communication along supply chains and provide certainty to investors. Other countries—notably Germany (with Industrie 4.0) and China are aggressively moving to create standards that benefit their domestic industries. Although no one suggested that the US government should prioritize its standard-setting efforts by adopting a top-down approach like that of China or Germany, there was sympathy/support for a more aggressive US posture. The discussion veered toward SMEs, which represent a large share of global value chains. SMEs will need incentives to drive engagement--participating in development and also in adoption of standards. One proposal involves expanding the scope of the R&D tax credit to include firm involvement in standard setting activities.
Trade Policy.Smart factories link digital technologies with production processes. The technologies underpinning smart factories (e.g., 3D printing, IIoT, etc.) will transform trade in manufactured goods. Given this transformation, policymakers should update trade policies and agreements and should develop interoperable norms governing data. However, only two trade agreements, CPTPP and NAFTA 2.0—neither of which is yet in effect—include provisions governing cross-border data flows. Nations are not approaching these issues uniformly. Whereas the US policy is to support a free flow of information across borders, the EU is regulating (restricting the use of) certain types of personal data, and other countries (e.g., China) are restricting the flow of all information (e.g., data localization requirements). Trade disputes have and will continue to arise and be decided before digital trade policy evolves enough to give manufacturers greater certainty.
Meeting Summary
Two clear themes—and questions about the appropriate role of the US government—emerged from the meeting:
Collective action is needed to create information governance conducive to investment. Much of this collective action will or could be initiated by manufacturers themselves, working in coordination with government, or by service providers. For example, the increasing availability of cybersecurity insurance is driving best practices to reduce vulnerabilities. But in some policy areas of import, proactive steps by manufacturers are difficult to recommend. In these cases, governmental action will provide regulatory certainty that drives investment. For example, with respect to trade policy, rules on cross-border data flows will eventually emerge through new trade agreements and the resolution of digital trade disputes.
Policy makers should better understand the needs of manufacturers before proposing specific solutions. Manufacturers have unique characteristics that policy makers ought to be aware of as they try to advance information governance. Specifically, these characteristics include the distinction between IT and OT (which has implications for cybersecurity), the complexity of 21stcentury value chains (e.g., the need for information flow within and across global value chains), and the capabilities of smaller firms (e.g., to participate in standard setting development and adoption) in relation to OEMs. Public policy must be informed by such considerations or it is likely to fall short of its goals.
Participants raised pertinent questions about the role of the US government: Is the US doing enough to provide the certainty that investors need? Is greater coordination needed among various US government agencies? Does the US need a mid-course assessment of its approach in light of the actions of other leading manufacturing countries (e.g., China, Germany)?
The U.S. government has labeled smart manufacturing as a priority. In October, the White House National Science and Technology Council released its Strategy for American Leadership in Advanced Manufacturing.One of its three goals is to develop and transition to new manufacturing technologies by capturing the future of intelligent manufacturing systems. The strategy calls for US leadership in promoting innovation in smart manufacturing technology. But this may not be sufficient. To facilitate timely U.S. investment in new technology, issues of information governance must also be addressed.
Keith B. Belton is the Director of the Manufacturing Policy Initiative at Indiana University in Bloomington, Indiana.
Peer reviewers: Chris Peters, CEO, The Lucrum Group, and Stephen Gold, President and CEO, Manufacturers Alliance for Productivity and Innovation (MAPI)
For further reading:
Belton, Keith. 2018. “What’s Stopping the Smart Factory Revolution?” Industry Week, June 4.
Capgemini Digital Transformation Institute. 2017. Smart Factories: How can manufacturers realize the potential of the digital revolution? Capgemini Consulting.
Frere, Eric; Zureck, Alexander; and Rohrig, Katherina. 2018. “Industrie 4.0 in Germany: The Obstacles regarding Smart Production in the Manufacturing Industry,” Social Science Research Network, posted August 15, 2018.
McKinsey Global Institute. 2015. The Internet of Things: Mapping the Value beyond the Hype. McKinsey & Company.
National Science and Technology Council, 2018. Strategy for American Leadership in Advanced Manufacturing, Office of Science and Technology Policy, October.
Shackelford, Scott. 2018. “Smart Factories, Dumb Policy? Managing Cybersecurity and Data Privacy Risks in the Industrial Internet of Things,” Social Science Research Network, posted October 14, 2018.
