Three Stages of Overcoming Supply Chain Disruption

If your organization’s success depends on its supply chain performance, the pandemic has likely exposed the major weak points in your business processes. The abrupt pause of manufacturing, shipping and distribution has led to thousands of containers stuck at ports, millions of workers temporarily out of work and purchase orders canceled or paused. The pressure on companies to meet demand against all odds remains high, and only the most prepared are coming out on top.

When vaccines prompted economic recovery, the rise in demand for goods and services led to a rapid business contraction and expansion cycle. As a result, companies across the globe now face a combined shortage of raw materials (like aluminum and lithium), required parts (like semiconductors) and skilled labor, all of which has additionally caused a spike in inflation.

What, then, is the key to overcoming the supply chain disruption and uncertainty caused by COVID-19? The solution can be broken down into three stages: stabilize, digitize and future-proof.


The first step is to solve the crisis at hand by analyzing the current areas of disruption, measuring the near- and long-term impacts of that damage and implementing the below initiatives to decentralize your supply chain:

  • Use data and analytics to measure vulnerabilities within the supply chain.
  • Prioritize the parts of your supply chain that are most relevant to high-margin or strategically important products.
  • Develop a multi-layered supply chain ecosystem for crucial parts.
  • Invest in initiatives toward decentralization by dispersing to multiple geographic locations.
  • Bring crucial manufacturing jobs back onshore.


If digital operations aren’t strengthened now, your organization will almost certainly continue to run into supply chain snarls in the future. Once you’ve established your core data and analytics processes, augment them by applying artificial intelligence, to help predict outcomes and assess supply chain gaps or input cost volatilities.

AI can also enhance automation to solve for the “human factor.” By improving the accuracy and productivity of robots, companies can alleviate the impacts of the labor shortage, leaving the monotonous tasks to the machines and freeing up existing human labor to perform more strategic and productive duties.

These solutions seek to improve time to market by addressing issues that slow the transfer of data and decisions, and, by extension, the flow of goods and services. However, human oversight is critical to addressing the unknown “X factor” (one that’s not included in the automation logic), to fill in any gaps that might otherwise generate an error.

Human-in-the-loop systems are critical to any form of automation, and especially important in the realm of AI, where full automation can lead to wild outcomes. Examples include the recent market drops caused by automated trading systems, or worse, fatal accidents caused by fully autonomous vehicles.


Once the supply chain mechanisms have been properly digitized and automated, we need to draw on emerging technologies like the internet of things, combined with ongoing global operations services, to monitor trends and react quickly when disruptions do occur. Start by taking these key actions:

  • Establish a global operations services team that is actively monitoring and improving supply chain processes.
  • Audit and update AI models to adjust for future “black swan” events or extreme commodity and input cost volatilities.
  • Continuously develop new ways to manage risk better, and ensure that contingency plans are in place.
  • Proactively build secondary and tertiary “intelligent” distribution networks.

Digitization of the supply chain, combined with a well-designed business strategy, can help alleviate current and future supply chain challenges, as well as improve business margins to prepare for future abrupt inflationary pressures.

While multiple attempts have been made to extend supply chain technologies beyond human analytics and overly mechanized supply chain automation, results have been mixed. This is because pure-play consulting firms are too focused on the development of process and application development, while technology vendors seek, by definition, to create one-size-fits-all solutions to a problem that warrants a more bespoke response.

Supply chain intelligence should incorporate a blend of people and technology. In the larger context of digital transformation, this blend is not only the best but the only solution that can be applied to create scalable, adaptable and sustainable supply chain solutions.