Operations
From Fragility to Resilience: COVID-19 Lessons for IOT Enabled Supply Chains
Nitin Joglekar, Associate Professor, Operations and Technology Management, is currently serving as an expert on advanced manufacturing and supply chains, within the Global Futures Council, at the World Economic Forum. This piece is based on his observations from the recently concluded Davos Conference that was aimed at shaping the principles, policies and partnerships needed towards Post-COVID-19 Recovery.
Nitin Joglekar, Associate Professor, Operations and Technology Management, is currently serving as an expert on advanced manufacturing and supply chains, within the Global Futures Council, at the World Economic Forum. This piece is based on his observations from the recently concluded Davos Conference that was aimed at shaping the principles, policies, and partnerships needed towards Post-COVID-19 Recovery.
Internet of Things (IOT) technologies, such as smart sensors integrated with AI tools, have been espoused as the future of manufacturing in SMART factories. However, their acceptance has been sparse – largely taking place at the level of point solutions, and pilot projects, within manufacturing systems in a variety of industries. What have we learned about the response of such emergent IOT-enabled systems during the COVID-19 crisis?
Key observations have been around the fragility of manufacturing and supply chain systems (e.g., see initial report). Aside from the early indicators of shortages for PPEs and toilet paper, some systematic trends have been identified: (i) severe job losses in sectors such as in non-essential retail, with a disproportionate share of these job losses occurring among women and within the lower-skilled workforce; (ii) disparities, both global and local, in accessing direly needed items such as vaccines; and (iii) breakdowns in the cyberinfrastructure needed for coordinating demand and supply mismatches.
This fragility has provided opportunities to identify resilient responses, initially within healthcare supply chains and now through emergent sectors such as biologics and electric cars. Most of the early responses in healthcare supply chains came through design thinking and prototyping of PPE that leveraged 3D-printing technologies (e.g., HP’s introduction of customized masks in Spain), proactive production adjustments needed to create low-cost vaccines (e.g., at the Serum Institute in India), planning the delivery of health services (e.g., use of predictive systems and early alert platforms in China), and training personnel for distributed delivery (e.g., J&J had to plan for 100 sites and 300 distribution centers). A second source of this resilience was evident in the broadening of the applications for “digital twins.” Earlier usages of such twins were focused on simulations to understand bottlenecks within factories. Post-COVID-19 usages of digital twins (e.g., at Siemens) have focused on integrating the sensors and data sources across entire value networks so that the response times for spare parts services, remote support, and industrial security services have been significantly improved. A third trend, perhaps counter-intuitive, has been the focus on sustainability and inclusiveness. For instance, as the demand of conventional transportation dwindled, several automotive firms (e.g., GM and Hyundai) have stepped up their commitment to electric vehicles. This year’s Davos Agenda Week also highlighted the growing commitment to ESG (Environmental, Social and Governance) goals through specific initiatives that would shape supply chain performance, such as:
- Using distributed blockchain technology to track and reduce emissions (see details)
- Fostering a multi-generational inclusive workforce (see details)
- Bringing racial justice to the workplace (see details)
That is, opportunities for harnessing IOT and allied digital options for improving supply chain performance, as observed through COVID-19 related moves, have been associated with distributed outcomes. Resilience has been gained through platformed supply chains, and system-wide solutions, rather than limiting digital implementations to within factory or point solutions. There are several barriers for development of such distributed outcomes. Direct employment in goods production accounts for nearly 12% of the U.S. workforce and it generates an additional 12% employment in sectors such as retail and transportation. Many of the underlying jobs and allied operating processes will have to be redesigned to take advantage of the distributed IOT capabilities (e.g., see 2020 Future of Jobs Report). A second barrier to change will be around shifts in sourcing policies. While there have been some conversations about deglobalization (e.g., increasing manufacturing near-shoring), experts at Davos were much more concerned about collaborative technologies and distancing-based work processes leading to an increase in the offshoring of service operations jobs. Finally, there was a fair amount of discussion about new types of business models and metrics needed for measuring and managing the organizational and economic changes that must be put in place to leverage these IOT-enabled resilient supply chains.
The overall takeaways are clear: the COVID-19 crisis has highlighted the need for IOT-enabled resilient supply chains. Resilient and distributed outcomes will require much experimentation, not only in healthcare but also in a variety of settings including construction, food, luxury goods, and sustainable transportation. At the core, these IOT implementations are complex organizational challenges spanning infrastructure, process, and technology management. Some conventional tasks may either be automated or will not be a part of Post-COVID-19 work. The tricky part for the workforce is likely to be acquiring new types of problem-solving skillsets. Students, who are getting trained not only in supply chain management principles but also in digital technologies and ESG (Environmental, Social, and Governance) leadership, should be well-positioned to take advantage of this opportunity.
