April 9, 2020 | Written by: Jonathan Wright
Categorized: COVID-19 | Supply Chain
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AI and other emerging technologies can help businesses maintain supply-chain continuity.
The COVID-19 contagion has caused a major slide in manufacturing and disrupted the supply chain for many companies across the globe. While the immediate focus is on maintaining the supply and meeting customer needs—often through hands-on rigorous work—leaders should also analyze the current pain points to plan for future disruptions.
Most supply chain leaders are still in the reactive phase of how to deal with this pandemic. That includes combating fear and uncertainty around shortages and gauging the overall impact the coronavirus will have on supply chain and logistics operations. Given the extraordinary costs many businesses are facing, however, they should start to identify actions now that will improve their resilience.
No one can predict the future. But we can be much smarter and strengthen the global supply chain by leveraging the power of AI and other emerging technologies that can help companies maintain business continuity amid disruption and uncertainty. According to a new IBM Institute for Business Value report, “COVID-19 and Shattered Supply Chains,” supply chains should be dynamic, responsive and interconnected to an organization’s ecosystem and processes. This requires end-to-end visibility, real-time insights and decisive actions—particularly in escalating situations.
The Predictive Power of AI
Using AI, organizations can turn unstructured real-time data into insights that help predict disruptions and vulnerabilities, providing near-term visibility. When it comes to IBM Systems’ own supply chain, we developed a cognitive control tower capability to help us identify early warnings based on external data, including social media and The Weather Company insights. This allows our supply chain professionals to have relevant and actionable information at their fingertips—enabling them to quickly respond and focus their attention on higher value activities like communicating with customers, suppliers and other impacted stakeholders rather than chasing information and status reports.
With AI, supply chain professionals can optimize orders based on factors like inventory reallocation and prioritization. This allows teams to react faster and shave off hundreds of person hours previously spent collecting data so that they can focus on that higher value work.
Supply chains have evolved into a network of hundreds of suppliers, sub-contractors and distribution centers, which are dispersed all over the world. Even the smallest upset can create a dramatic and resonating effect on the global supply network. Over the last decade, many organizations have been impacted by some major issues that caused ripples throughout the global supply chain, such as the 2010 eruption of Iceland’s Eyjafjallajökull volcano, or the 2011 Tohōku, Japan earthquake and tsunami, or the flooding in Thailand later that same year. What we have learned is that no company can afford not to have a multi-dimensional, dynamic supply strategy that is capable of responding to disruption.
As organizations continue to move toward intelligent, self-correcting supply chains, there are three strategies to consider:
Re-evaluate the sourcing strategy and redesign the supplier network: Balance between the level of risk the enterprise can tolerate and the amount of operational flexibility it wants to achieve. Use AI to leverage unstructured real-time data to provide alerts to help predict disruptions and vulnerabilities and to provide visibility and insights for recommended corrective actions.
As an example, The Master Lock Company, the largest global manufacturer and marketer of padlocks and personal safes, recently onboarded a significant number of additional global partners. The company chose IBM to migrate its electronic data interchange (EDI) to IBM Sterling Supply Chain Business Network—a security-rich, cloud-based solution for trading partner integration.
Build smarter supply chain modeling and scenario analysis: Use digital twins to provide both immediate assessment and the longer-term ability to continually evaluate the fine balance between lean operations and risk mitigation. Using analytics, AI, and visualization tools, it’s possible to model and then build flexibility and optionality into structural supply chains. In Europe, we are working with a client to develop a heat map for their suppliers to know where the current pandemic is impacting their business, allowing them to make real-time decisions and immediate order changes.
Set up data-sharing platforms: Allow strategic partners to quickly collaborate and understand the impact of disruptions. Leverage AI to support rapid scenario planning and unlock hidden insights that augment the supply chain planner’s abilities to quickly determine options and take action. We recently worked with Lenovo, which took part in the Watson™ Supply Chain Fast Start program. Within five weeks, the IBM team helped Lenovo complete three AI-driven use-case analyses using supply chain data from its production system.
Supply chain professionals are confronting and will continue working through the immediate challenges they are facing during this pandemic. These organizations are learning how to better manage, foresee and limit the severity of disruptions by building the capabilities necessary to respond to future events with both speed and certainty.