Coronavirus makes us look at technology to combat supply chain risks
Somehow, businesses never learn. Two years ago, Munich Re, the reinsurance giant, tried to start underwriting a new kind of insurance which would help rebuild a company if its business wasdestroyed in an epidemic. There were few takers. Today there’s a rush; but who’s going to insure a burning house. After the March 2011 earthquake and tsunami in Fukushima, Japan, many MNCs learned painful lessons about the vulnerabilities in their supply chains and the severe financial impact of those. But they are again blindsided by the Coronavirus crisis.
While they could somehow figure out the impact of their direct suppliers, it was the influence of the second and third tier suppliers in the affected region, which turned out to be equally serious. Once again, the world’s major companies have been caught off guard by the Coronavirus epidemic, as they seldom formalized these often invisible second & third tier relationships.Many firms, often due to a lack of options, are also overly reliant on single-sourcing for several primary or intermediate goods. Unsurprisingly, most of these are also based in virus-affected regions of China.
Current numbers show that over 12,000 facilities – including warehouses, factories and other operations – owned by the world’s 1000 largest companies – are based in quarantined areas such as China, Italy or South Korea, with China accounting for over 86%. This has sparked global recessionary fears. The Organization of Economic Cooperation and Development (OECD), forecast that if Coronavirus spreads then global growth could plummet to 1.5% from 2.9%projected earlier. This is very real as China accounts for almost 16% of the world GDP.
Advising companies to develop multiple supply sources and production facilities is like closing the barn door after the equine creature has bolted. There are new risk management technologies using AI and natural-language processing to address global supply chain and logistics challenges. These technologies are proving to be a game changer. McKinsey expects businesses to gain between $1.3 trillion and $2 trillion a year in economic value by using AI in their supply chains.
AI, bundled with technologies such as Machine Learning, the Internet of Things (IoT), and predictive analytics, can created powerful algorithms to address these challenges. Access to additional data gives companies a better picture of their global logistics networks. This degree of transparency is critical because it acknowledges that the way we think about supply chain management and logistics is changing. One hopes that organizations will now focus on these solutions, having learnt their lesson the hard way.
