Many organisations will use the lessons learned from the COVID-19 crisis to build resilience within their supply chain networks.

They will be able to apply the use of analytics and data insights to anticipate disruptions and proactively restructure supply chain flows and network design. By utilising data analytics, machine learning and smarter technologies to predict disruptions and risk events, supply chain leaders can adopt predictive supply chain risk management and scenario planning approaches to minimise the impact of potential future disasters.

Over reliance on global supply chains for raw materials, key components to finished goods and the consequential impact of any disruption to those supply chains has seen some organisations move towards micro supply chains.

From an operations strategy perspective, micro supply chains are best characterised as a make/assemble-where-you-sell-and-buy-where-you make/assemble approach. Along with the impacts of COVID-19, recent geopolitical events, such as Brexit and the still unfolding US-China trade challenges, organisations are accelerating the way that supply chains are restructured. There is now a greater focus on leveraging local production capacity to enable flexible, agile and sustainable supply chains.