Stress Testing for the Next Supply Chain Disruption
A crisis like the 2020 pandemic often shines a spotlight on underlying systemic weaknesses, and the pandemic certainly brought the fragility of our supply chain to center stage. In recent years, we had seen prior regional calamity—such as the 2011 earthquake and tsunami in Japan—cause global ripples in the supply chain, which highlighted the existing weaknesses to our interconnected commerce networks. So when these “potential” problems of the global supply chain became very real, most industry professionals weren’t surprised by its fragility. After all, running lean supply chains with low inventory and just-in-time delivery was a feature, not a bug.
It would be easy (and incorrect) to write off today’s challenges as the result of a once-in-a-lifetime health emergency, with a variety of rare factors that swirled together to create a perfect storm of lost production and transportation, radical shifts in demand and unpredictable recovery timelines. But I think it’s also instructive to focus on a single event from the past 18 months: the Suez Canal blockage. One of the world’s busiest trade routes was completely blocked for almost a week because a single ship ran aground. That’s not a black-swan event; it could happen again. Even in a pre-pandemic economy, that single event would have created weeks of ripples across the global supply chain.
The fragility of the global supply chain has never been more top-of-mind than it is now, and it’s time to focus our efforts on more than just restoring our previous capabilities. Instead, we need to build new levels of resiliency into our networks of suppliers and stakeholders. Those capabilities require a hard look at how we collect and use data from across our network, and digitalization investments that can empower businesses to predict and pivot when disruption occurs. I believe that strategic investments in virtual twins and IT infrastructure that powers them is the key to ensuring supply chain stability and creating opportunities for growth when the next crisis hits.
Visibility & Flexibility
It’s safe to say the supply chain is no longer an overlooked or underappreciated part of the business. Over the past decade, the explosion of e-commerce and consumer expectations ran headlong into the natural disasters and geopolitical uncertainty of our world, and the C-Suite began appreciating robust supply chains as truly strategic differentiators. The pandemic served as an accelerator, putting supply chain top of mind for every business leader. A mid-pandemic IT spending survey from IDC found 57% of respondents had their supply chains “significantly affected,” while another 27% said they were anticipating supply chain disruption soon.
The IDC survey also highlighted “resiliency” as a top supply chain concern, followed closely by a lack of digital competence to transition supply chains into new business models. The resiliency of your business dictates whether the gap between a business’ slowdown and its eventual recovery will be a wide canyon, or a small trench that can be overcome with smart decisions informed by the right information. But those survey responses indicate many businesses don’t believe they have the right digital tools or expertise to pivot their supply chain operations in the face of disruption or shifts in business focus (e.g., the ability to shift production from producing paper products to nasal swabs).
That inability to respond to change quickly is a problem that needs to be addressed. By using virtual environments to create a collaborative system where all stakeholders can see what’s happened in the past and what’s happening right now, businesses can create simulations to analyze and optimize their paths forward--and find the resiliency to weather a coming storm.
Finding the Data
A virtual twin is commonly associated with virtual replicas of physical machines, such as a shop floor assembly line. If you already have a network of IoT sensors on your shop floor or assembly line feeding real-time operations information, you’re off to a good start. Applying the virtual twin concept to the supply chain requires extending those IoT sensors and data-capture methods beyond the walls of your manufacturing or distribution center, and into warehouses and suppliers to track inventory and transit times.
As you begin capturing real-time data from your suppliers, it’s time to establish the goals of your virtual supply chain twin, which can be a daunting question. As always, the first critical analysis should be around the business goals that have the highest priority, and letting those priorities determine your focus. For example, industries where product innovation is accelerating and time-to-market is the key factor would have different priorities than rapid growth industries (like battery-cell manufacturing) where a supply chain might need to quickly ramp-up to support new facilities.
Armed with forecast data and a robust virtual twin of their supply network, decision-makers can begin running simulations to stress-test the organization. Of course, virtual twins can also provide insights into overall process optimization, but within our post-pandemic mindset, business leaders would be wise to use these virtual twins to answer some “what if” scenarios. Testing granular constraints of resources, materials and bottlenecks are essential for contingency planning. Remember to not only troubleshoot potential disruptions to your supply, but also to your demand, as we’ve seen business and consumer buying habits can shift radically in a crisis.
Technology isn’t a silver bullet for a resilient supply chain, but the right IT infrastructure is certainly a critical piece. It’s important to underscore that the effectiveness of your supply chain virtual twin hinges on the quality of the data fed into the model. As your business gains visibility and the ability to simulate supply chain scenarios in pursuit of resiliency, it’s also possible to gain strategic business insights as well. For example, Latécoère, a tier 1 partner for the aviation industry, was hindered by component bottlenecks from external suppliers. Following a simulation of the company’s supply chain and seeing the effects of tweaking the interconnected variables of their production and distribution facilities, Latécoère determined that shifting to in-house component production would be the most cost-effective strategy. With data to back up their decision, and a virtual twin to guide the construction of new production lines, Latécoère invested in their own manufacturing capabilities and their supply chain remained steady.
Planning for Whatever Comes Next
Until 2020, we hadn’t fully reckoned to how our interconnected global economy would respond to widespread and prolonged stress. As the pandemic recovery continues, now is the time for investments and new best practices. It might be time for businesses to look at the value of focusing more on resiliency rather than raw efficiency or keeping some extra inventory in the system for “just in case” rather than “just in time.”
But the lessons we learn aren’t going to change the fundamentals of our industry. If supply chain managers have the agility to respond both proactively and reactively to a demand or supply disruption and can present that insight to decision-makers sooner than anyone else, that business will have a competitive advantage. Virtual twins provide the framework for stress-testing in preparation for the next global disruption. Whether it’s a stuck ship causing a global traffic jam or a natural disaster, companies that invest in resiliency will be positioned to make adjustments and emerge from the crisis stronger than before.
Eric Green, vice president of marketing for Dassault Systèmes, brings 27 years of manufacturing, supply chain and enterprise software experience in his role managing DELMIA user experience, brand marketing and business development. Under his previous leadership at Apriso Corp., marketing, industry and solution development significantly contributed to Apriso’s growth and market leadership in manufacturing operations software.
